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website/docs/usage/processing-pipelines.md
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@ -1273,7 +1273,7 @@ loss is calculated and to add evaluation scores to the training output.
| [`update`](/api/pipe#update) | Learn from a batch of [`Example`](/api/example) objects containing the predictions and gold-standard annotations, and update the component's model. | | [`update`](/api/pipe#update) | Learn from a batch of [`Example`](/api/example) objects containing the predictions and gold-standard annotations, and update the component's model. |
| [`initialize`](/api/pipe#initialize) | Initialize the model. Typically calls into [`Model.initialize`](https://thinc.ai/docs/api-model#initialize) and can be passed custom arguments via the [`[initialize]`](/api/data-formats#config-initialize) config block that are only loaded during training or when you call [`nlp.initialize`](/api/language#initialize), not at runtime. | | [`initialize`](/api/pipe#initialize) | Initialize the model. Typically calls into [`Model.initialize`](https://thinc.ai/docs/api-model#initialize) and can be passed custom arguments via the [`[initialize]`](/api/data-formats#config-initialize) config block that are only loaded during training or when you call [`nlp.initialize`](/api/language#initialize), not at runtime. |
| [`get_loss`](/api/pipe#get_loss) | Return a tuple of the loss and the gradient for a batch of [`Example`](/api/example) objects. | | [`get_loss`](/api/pipe#get_loss) | Return a tuple of the loss and the gradient for a batch of [`Example`](/api/example) objects. |
| [`score`](/api/pipe#score) | Score a batch of [`Example`](/api/example) objects and return a dictionary of scores. The [`@Language.factory`](/api/language#factory) decorator can define the `default_socre_weights` of the component to decide which keys of the scores to display during training and how they count towards the final score. | | [`score`](/api/pipe#score) | Score a batch of [`Example`](/api/example) objects and return a dictionary of scores. The [`@Language.factory`](/api/language#factory) decorator can define the `default_score_weights` of the component to decide which keys of the scores to display during training and how they count towards the final score. |
<Infobox title="Custom trainable components and models" emoji="📖"> <Infobox title="Custom trainable components and models" emoji="📖">